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Article
An interpretable neural network for robustly determining the location and number of cluster centers
K-means is a clustering method with an interpretable mechanism. However, its clustering results are significantly affected by the location of the initial cluster centers. More importantly, for it and its impro...
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Chapter and Conference Paper
Theory-Guided Convolutional Neural Network with an Enhanced Water Flow Optimizer
Theory-guided neural network recently has been used to solve partial differential equations. This method has received widespread attention due to its low data requirements and adherence to physical laws during...
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Article
Open AccessMonte Carlo Tree Search: a review of recent modifications and applications
Monte Carlo Tree Search (MCTS) is a powerful approach to designing game-playing bots or solving sequential decision problems. The method relies on intelligent tree search that balances exploration and exploita...
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Article
Open AccessAn overview of mixing augmentation methods and augmentation strategies
Deep Convolutional Neural Networks have made an incredible progress in many Computer Vision tasks. This progress, however, often relies on the availability of large amounts of the training data, required to pr...
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Chapter and Conference Paper
Monte Carlo Tree Search with Metaheuristics
Monte Carlo Tree Search/Upper Confidence bounds applied to Trees (MCTS/UCT) is a popular and powerful search technique applicable to many domains, most frequently to searching game trees. Even though the algor...
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Chapter and Conference Paper
StatMix: Data Augmentation Method that Relies on Image Statistics in Federated Learning
Availability of large amount of annotated data is one of the pillars of deep learning success. Although numerous big datasets have been made available for research, this is often not the case in real life appl...
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Chapter and Conference Paper
Prediction of the Facial Growth Direction: Regression Perspective
First attempts to predict the direction of facial growth (FG) direction were made half a century ago. Despite numerous attempts and elapsed time, a satisfactory method has not been established yet, and the pro...
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Chapter and Conference Paper
LQ-R-SHADE: R-SHADE with Quadratic Surrogate Model
The application of evolutionary algorithms in continuous optimization is a well-studied area of research. Nevertheless, recently there have been numerous works associated with surrogate-assisted approaches. Th...
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Chapter and Conference Paper
Evolutionary Approach to Melodic Line Harmonization
The paper presents a novel evolutionary algorithm (EA) for melodic line harmonization (MLH) - one of the fundamental tasks in music composition. The proposed method solves MLH by means of a carefully construct...
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Chapter and Conference Paper
Towards Frugal Artificial Intelligence: Exploring Neural Network Pruning and Binarization
Recently, it has been stipulated that training larger and larger models, using ever increasing datasets is not sustainable in a long-run. Hence, the idea of Frugal Artificial Intelligence has been put forward....
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Chapter and Conference Paper
Surrogate-Assisted LSHADE Algorithm Utilizing Recursive Least Squares Filter
Surrogate-assisted (meta-model based) algorithms are dedicated to expensive optimization, i.e., optimization in which a single Fitness Function Evaluation (FFE) is considerably time-consuming. Meta-models allo...
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Chapter and Conference Paper
Human-Level Melodic Line Harmonization
This paper examines potential applicability and efficacy of Artificial Intelligence (AI) methods in automatic music generation. Specifically, we propose an Evolutionary Algorithm (EA) capable of constructing m...
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Chapter and Conference Paper
Coevolutionary Approach to Sequential Stackelberg Security Games
The paper introduces a novel coevolutionary approach (CoEvoSG) for solving Sequential Stackelberg Security Games. CoEvoSG maintains two competing populations of players’ strategies. In the process inspired by ...
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Chapter and Conference Paper
Learning Attacker’s Bounded Rationality Model in Security Games
The paper proposes a novel neuroevolutionary method (NESG) for calculating leader’s payoff in Stackelberg Security Games. The heart of NESG is strategy evaluation neural network (SENN). SENN is able to effecti...
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Chapter and Conference Paper
Adversarial Defenses via a Mixture of Generators
In spite of the enormous success of neural networks, adversarial examples remain a relatively weakly understood feature of deep learning systems. There is a considerable effort in both building more powerful a...
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Chapter and Conference Paper
Prediction of the Facial Growth Direction is Challenging
Facial dysmorphology or malocclusion is frequently associated with abnormal growth of the face. The ability to predict facial growth (FG) direction would allow clinicians to prepare individualized therapy to i...
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Chapter and Conference Paper
Towards Human-Level Performance in Solving Double Dummy Bridge Problem
Double Dummy Bridge Problem (DDBP) is a hard classification problem that consists in estimating the number of tricks to be taken by N-S pair during a bridge game. In this paper we propose a new approach to DDB...
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Chapter and Conference Paper
A Committee of Convolutional Neural Networks for Image Classification in the Concurrent Presence of Feature and Label Noise
Image classification has become a ubiquitous task. Models trained on good quality data achieve accuracy which in some application domains is already above human-level performance. Unfortunately, real-world dat...
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Chapter and Conference Paper
Biologically Plausible Learning of Text Representation with Spiking Neural Networks
This study proposes a novel biologically plausible mechanism for generating low-dimensional spike-based text representation. First, we demonstrate how to transform documents into series of spikes (spike trains) w...
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Chapter
MCTS/UCT in Solving Real-Life Problems
Monte Carlo Tree Search (MCTS) supported by the Upper Confidence Bounds Applied to Trees (UCT) method, i.e. MCTS/UCT, since its onset in 2006, has been one of the state-of-the-art techniques in game-playing do...
